ArticleMedical and veterinary entomology2025
Modelling vector and host distributions to inform potential disease risk: A case study of West Nile virus in the United Kingdom.
Article in Medical and veterinary entomology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Climate-based forecasting from national Culex mosquito surveillance to support West Nile and Usutu virus preparedness in England and Wales.BMC public health · 2026Article
- Modelling vector and host distributions to inform potential disease risk: A case study of West Nile virus in the United Kingdom.Medical and veterinary entomology · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Vector-borne diseases pose significant global threats to both human and animal health, and their impacts are expected to intensify with ongoing climate change. Understanding the ecological and environmental drivers of these diseases is essential for developing effective surveillance and control strategies. Central to this is knowledge of the distributions of vectors and hosts, and how these may shift in response to environmental changes. In this study, we present a generalisable framework for predicting the current and future distributions of vectors and wildlife hosts using correlative modelling approaches. We integrate these predictions with data on livestock and human populations to inform the potential risk of West Nile virus (WNV) establishment and exposure in the United Kingdom. Currently absent from the United Kingdom, WNV is an orthoflavivirus maintained in a natural transmission cycle between mosquitoes and birds. Spillover into incidental hosts such as humans and horses can result in febrile illness, with severe cases leading to encephalitis and death. Our findings identify regions at elevated risk of WNV establishment where competent avian hosts and mosquito vectors are likely to co-occur and where infected vectors may interact with spillover hosts. We also explore how these risk patterns may evolve by 2100 under different environmental scenarios. Across all scenarios, risk is projected to increase in the south-east of the United Kingdom and decline in northern regions. This work demonstrates how modelling current and future vector and host distributions can inform risk assessments for emerging vector-borne diseases. Such insights are critical for guiding policy decisions and enhancing preparedness for disease incursions in a changing environment.
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